Research by Pradeep K. Chintagunta, Jean-Pierre Dubé,
and Puneet Manchanda

Banner advertising helps companies retain customers by
bringing them back to a company's Web site faster and encouraging
them to spend more.

Total spending on Internet advertising now exceeds spending
on some traditional media, but despite the quick adoption
of online marketing by many firms, remarkably little is known
about the potential payoffs of such efforts.

Most online advertising exists in the form of banner ads,
which combine graphics, text, and a link to an advertiser's
Web site. Consumers access the advertiser's site by clicking
on the banner ad, which is referred to as "clickthrough."
In the early days of e-commerce, the fact that consumer behavior
in response to advertising could be measured instantaneously
and objectively by calculating the clickthrough rate was seen
as an exciting development. However, clickthrough rates typically
have been less than one percent of all exposures. In addition,
these rates only measure visits to a site, ignoring actual
purchasing behavior. Previous research has shown that few
visits translate into actual purchases.

University of Chicago Graduate School of Business professors
Pradeep K. Chintagunta, Jean-Pierre Dubé, and Puneet
Manchanda, together with doctoral student Khim Yong Goh suggest
that, as in traditional advertising, exposure to banner ads
may result in purchase behavior after a temporal gap.

"Most theories of advertising note that the effects
of advertising are not immediate," says Manchanda. "We
therefore wanted to link individual exposure to banner advertising
to individual behavior while allowing for a temporal gap.
Our approach expands upon the work of previous studies that
have only documented attitudinal changes as a function of
exposure to Internet advertising."

The authors report their findings in their recent study,
"The Effects of Banner Advertising on Consumer Inter-purchase
Times and Expenditures in Digital Environments."

The authors find that banner ads are effective for bringing
existing customers back to a Web site sooner to make additional
purchases. Thus, in any given period of time, current customers
who were exposed to banner advertising are likely to spend
more money than customers who were not. The authors also suggest
that the industry-wide practice of judging banner ads by the
number of clicks they generate understates the effectiveness
of banner ad campaigns.

"If you just measure clicks, you are not capturing the
real effect of advertising," says Dubé. "What
you want to see is whether people are purchasing items."

Even though banner ads are typically regarded as doorways
to bring in new customers, the long-term viability of a Web
site depends on its ability to retain customers. Many industry
studies have shown that retaining current customers, relative
to acquiring new customers, is more profitable to a firm over
the lifetime of the customer. For online firms, the question
then becomes whether banner advertising can modify the behavior
of repeat customers as they become more experienced with the
firm's Web site.

"Online advertising budgets have been shrinking since
the dot-com bust," says Dubé. "It's a known
fact that it's cheaper to market to a current customer than
a new customer. Our study shows you can use banner ads to
stimulate business in your repeat customer base."

Following the Cookie Trail

What distinguishes Internet advertising from traditional
advertising is the ability to match individual advertising
exposure to individual consumer behavior. If a consumer sees
a television commercial for a product, it is very difficult
to then match up the commercial with whether or not a consumer
purchases the advertised product in a store. The Internet
allows researchers to put the whole story together, from awareness
building through actual purchasing, going beyond what is possible
in the traditional world.

The technology that makes this possible is based on small
files called "cookies" that are stored on an individual
consumer's computer once they visit a Web site. By keeping
track of cookies, firms have detailed data on when, where,
and to how many ads each individual cookie was exposed. This
advertising data can then be matched up with purchases made
via that computer. Advertisers can therefore return to their
clients and let them know which cookie actually resulted in
a purchase, and how many dollars that cookie generated.

Beyond Clicks

Chintagunta, Dubé, Manchanda, and Goh use data from
an Internet-only firm that sold healthcare and beauty products
as well as nonprescription drugs. Their data spans a period
of three months during the third quarter of 2000. Most data
used for studying online environments feature browsing behavior
only. Their new dataset is unique because the authors are
able to measure individual stimulus (advertising) as well
as response (purchase visits and dollars spent).

The majority of the company's banner ads focused on brand-building,
and typically consisted of the name of the Web site and a
line describing the benefits of purchasing from the site.
More than 80 percent of the company's advertising activity
during this period was on portal and alliance Web sites such
as Yahoo!, America Online, Women.com, iVillage.com, Healthcentral.com,
and E*Trade. A given banner ad typically appeared on these
sites over several weeks.

To ensure that they only included repeat customers in their
analysis, the authors used data from customers that had made
at least two purchases from the site. The final sample consisted
of 2,192 cookies.

Industry measures such as clickthrough only account for direct
action, rather than measuring the awareness building that
takes place over an advertising campaign. The authors therefore
allowed for the possibility of customers seeing an ad, mulling
it over, and then returning to make a purchase after a period
of time.

The behavior of repeat customers was measured using statistical
models that captured purchase timing (when to visit) and purchase
expenditure (how much to spend on a purchase visit). The authors
measured the effect of the following advertising variables:
the time between purchases and dollars spent; the amount of
advertising exposure; the time since consumers last saw an
ad; where they saw the ad; and the ad copy and graphics they
saw for each banner (the "creative").

The authors find that seeing the ads more frequently brought
customers back to shop sooner. The more recently consumers
saw an ad, the faster they came back to buy. Exposure to banner
ads at more Web sites also had a similar effect. However,
exposure to a higher number of ads with different creative
treatments delayed consumers' return to the Web site. For
purchase expenditure, the effect of advertising is small.
Instead, the best predictor of current expenditure tended
to be the amount spent on the last shopping occasion.

The authors also find differences among the shopping behavior
of repeat customers. Their data and statistical model indicate
that the Web site's customers can be classified into three
different segments. Customers in these segments are affected
differently by the frequency of banner advertising, how recently
they saw the banner ads, and the monetary value of their past
purchases. The largest segment consists of loyal but infrequent
shoppers, followed by a segment comprised of relatively frequent
purchasers. There is also a small segment of impulse shoppers
who tend to shop on the same day that they are exposed to
a banner ad.

Overall, for most consumers in the sample, the authors find
evidence of a temporal lag between exposure and action. They
speculate that this gap exists because banner advertising
acts as a brand building tool and reminds consumers to visit
a site.

Ingredients of a Good Campaign

The study provides insights into the nature of consumer response
to banner advertising. First, the authors find evidence of
temporal differences between exposure and behavior for a majority
of the consumers in the sample. This result implies that managers
can correctly evaluate the effectiveness of advertising campaigns
only if they account for this temporal gap.

Second, the time since last exposure and the number of creatives
has a much larger effect on purchase timing relative to the
number of exposures. Regarding advertising copy, exposing
the same consumer to several unrelated creatives may be less
beneficial than a single creative, assuming that all the creatives
are of the same quality.

"More companies are starting to realize that redundancy
is a good thing for their online advertising campaigns,"
says Dubé. "If you have a single, effective message,
it's easier for consumers to extract pertinent information
from your banner ad even as they are inundated with ads from
other sites."

In terms of the timing of advertising, it may be more useful
to expose consumers to a series of evenly spaced ads rather
than massed exposures. Given the strong same day purchase
effect resulting from advertising exposure, advertisers can
potentially use banner advertisements to smooth out sales
and run special promotions.

Finally, there seem to be strong positive benefits from ensuring
that customers are exposed to the same advertisement across
many Web sites.

"For the category of frequently purchased, nonseasonal
products in our study, steady and consistent advertising on
many different Web sites is the right managerial approach,"
says Manchanda.

In terms of the dollars spent on a visit, exposure to a variety
of creatives increases dollars spent while advertising across
many sites decreases dollars spent. However, in contrast,
exposure to more creatives delays repeat visits while exposure
on more sites brings consumers back sooner. Therefore, managers
need to optimize the number of creatives and advertising sites
by making the trade-off between quicker visits and lower expenditure
per visit, or slower visits and higher expenditure per visit.

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Pradeep K. Chintagunta is Robert Law Professor of Marketing
at the University of Chicago Graduate School of Business.
Jean-Pierre Dubé is assistant professor of marketing
at the University of Chicago Graduate School of Business.
Puneet Manchanda is associate professor of marketing at the
University of Chicago Graduate School of Business.